Although many efficient image cutout approaches have been proposed,it is still a challenge to cut out foreground objects from a video clip because of the costs of time and memory consumption and the difficulty in main...
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Although many efficient image cutout approaches have been proposed,it is still a challenge to cut out foreground objects from a video clip because of the costs of time and memory consumption and the difficulty in maintaining temporal coherence for the cutout *** this paper,we propose a novel and efficient video cutout approach by extending a multilevel banded image segmentation method to video *** our method,the segmentation results are propagated frame by frame at the lowest resolution level based on optical flow,and are refined in image pyramids level by level through banded graph *** construct an adaptive narrow band to ensure that the segmentation result falls exactly into the narrow band during *** results show that the video cutout approach based on adaptive multilevel bands dramatically reduces time and memory costs,and achieves ideal segmentation results.
As library-based techniques of virus and intrusion detection prove insufficient to be means of protection for computer systems and networks, alternate methods must be incorporated into computer defense. This paper sur...
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ISBN:
(纸本)1565553144
As library-based techniques of virus and intrusion detection prove insufficient to be means of protection for computer systems and networks, alternate methods must be incorporated into computer defense. This paper surveys a variety of Artificial Intelligence methods aimed at improving the effectiveness of modern computer security in the face of more prevalent, sophisticated, and ever-changing threats. Specifically, Artificial Immune Systems, Genetic Algorithms, Genetic Programming, and Neural Networks are discussed primarily within the auspices of threat analysis and system testing. Several implemented solutions are discussed and analyzed. Additionally, the paper provides suggestions for the synthesis of varying methods with traditional security in order to create a stronger, more robust security system.
In this paper we improve on the supervised classification method developed in Kornienko et al. (2002) by the introduction of Principal Components Analysis to the inference process. We also extend the classifier from d...
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This paper introduces a novel user classification task in the context of web user forums. We present a definition of four basic user characteristics and an annotated dataset. We outline a series of approaches for pred...
Reverse engineering of software systems often employs static analysis of a program's source code. In this invited talk, I will present our approach to reverse engineering of software systems via analyzing monitori...
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We consider stochastic games wherein players are striving to make optimal decisions but their decisions are subject to mistakes or random shocks. We assume that the players make decisions in the direction of higher pa...
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As software systems evolve by adding new extensions some unexpected conflicts may occur, which is known as the Feature Interaction Problem (FIP). FIP is a threat to the dependability of software systems as it can brea...
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N^(6)-Methyladenine is a dynamic and reversible post translational modification,which plays an essential role in various biological *** of the current inability to identify m6A-containing mRNAs,computational approache...
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N^(6)-Methyladenine is a dynamic and reversible post translational modification,which plays an essential role in various biological *** of the current inability to identify m6A-containing mRNAs,computational approaches have been developed to identify m6A sites in DNA *** to improve prediction performance,we introduced a novel ensemble computational approach based on three hybrid deep neural networks,including a convolutional neural network,a capsule network,and a bidirectional gated recurrent unit(BiGRU)with the self-attention mechanism,to identify m6A sites in four tissues of three *** a total of 11 datasets,we selected different feature subsets,after optimized from 4933 dimensional features,as input for the deep hybrid neural *** addition,to solve the deviation caused by the relatively small number of experimentally verified samples,we constructed an ensemble model through integrating five sub-classifiers based on different training *** compared through 5-fold cross-validation and independent tests,our model showed its superiority to previous methods,im6A-TS-CNN and iRNA-m6A.
In the past decades, technical developments have enabled the delivery of sophisticated mobile spatial audio signals to consumers, over links that range very widely in quality, requiring decisions to be made about the ...
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The log-structured merge-tree (LSM-tree)-based key-value store has been widely adopted by many large-scale data storage applications for its excellent write performance. However, such write performance gains mainly co...
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